Evaluating the performance of new approaches to spot quantification and differential expression in 2-dimensional gel electrophoresis studies.

Spot detection and quantification for 2-DE are challenging and important tasks to fully extract the proteomic information from these data. Traditional analytical methods have significant weaknesses, including spot mismatching and missing data, which require time-consuming manual editing to correct, dramatically decreasing throughput and compromising the objectivity and reproducibility of the analysis. To address this issue, we developed Pinnacle, a novel, quick, automatic, noncommercial method that borrows strength across gels in spot detection and has been shown to yield more precise spot quantifications than traditional methods.

The myth of automated, high-throughput two-dimensional gel analysis.

Many software packages have been developed to process and analyze 2-D gel images. Some programs have been touted as automated, high-throughput solutions. We tested five commercially available programs using 18 replicate gels of a rat brain protein extract.

Pinnacle: a fast, automatic and accurate method for detecting and quantifying protein spots in 2-dimensional gel electrophoresis data.

Motivation: One of the key limitations for proteomic studies using 2-dimensional gel electrophoresis (2DE) is the lack of rapid, robust and reproducible methods for detecting, matching and quantifying protein spots. The most commonly used approaches involve first detecting spots and drawing spot boundaries on individual gels, then matching spots across gels and finally quantifying each spot by calculating normalized spot volumes. This approach is time consuming, error-prone and frequently requires extensive manual editing, which can unintentionally introduce bias into the results.